The Deterministic Information Bottleneck

DOI10.1162/NECO_a_00961zbMath1478.68082arXiv1604.00268OpenAlexW2797548502WikidataQ38836891 ScholiaQ38836891MaRDI QIDQ5380714

David J. Schwab, Daniel J. Strouse

Publication date: 6 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1604.00268

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30) Measures of information, entropy (94A17)

Related Items (6)

Second-order information bottleneck based spiking neural networks for sEMG recognition ⋮ The Deterministic Information Bottleneck ⋮ Efficient mixture model for clustering of sparse high dimensional binary data ⋮ Statistical criticality arises in most informative representations ⋮ The Information Bottleneck and Geometric Clustering ⋮ Bounded rationality in learning, perception, decision-making, and stochastic games

Cites Work

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• A Maximum-Likelihood Interpretation for Slow Feature Analysis
• How Many Clusters? An Information-Theoretic Perspective
• 10.1162/153244303322753625
• Optimal causal inference: Estimating stored information and approximating causal architecture
• The Deterministic Information Bottleneck
• Elements of Information Theory

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